According to the Center for Food Safety and Applied Nutrition (2023), food waste in America is estimated at between 30 and 40% of the food supply. The waste of food itself is largely unpreventable, but what is done to the food when it is discarded is what is important in keeping food out of landfills. When in landfills, organic material (such as food) cannot decompose properly, and often will rot and produce methane, a greenhouse gas which contributes to global warming (Office of Resource Conservation and Recovery, 2020). According to the Office of Resource Conservation and Recovery (2020), 8% of global greenhouse gas emissions come from landfills.  

A solution that many countries around the world and cities in America have adopted is a strong composting system. Food is organic material, and organic material can be easily reused in many ways, most notably, as fertilizer for soil. A success story in America exists in the Californian city of San Francisco. In 2009, an ordinance was passed requiring recyclables, compostables, and trash to be disposed of separately (U.S. Environmental Protection Agency, 2023). The compost produced is given to local farmers, orchards, and vineyards for use, effectively giving back to the community (U.S. Environmental Protection Agency, 2023).  In addition to supporting local produce, this system allowed San Francisco to aim higher with their waste reduction efforts. 

Data plays an important role in overseeing the progress of the implementation of any new system. The EPA already does a lot of data collection to identify the primary sources of food waste, which is important in the initial problem identification stages. Not only can data be used to identify the problem, but it’s an important tool to support the continuous improvement of systems to reduce food waste. Without data, it’s difficult to identify new issues, or issues whose solution did not either fully address or eliminate the issue. 

The reduction of food waste not only supports the community, but it’s an important part of reducing greenhouse gas emissions and slowing global warming. Data plays a strong role in this issue, and it’s imperative that data scientists be included in conversations regarding food waste.

In 2023, George Washington University’s new Data Science for Sustainable Development Hub welcomes three summer research interns. The interns are supporting a project on local-level eco-labeling. This project will argue that eco-labeling should consider environmental conditions on the ground to be most effective, discrediting national- or global-level ecolabeling regimes. The project aims to highlight the importance of tailoring eco-labeling to specific local contexts.

Aditya Kumar, an MS student in the GW Data Science Department, will focus on building a city-level ecolabel for Washington DC. Aditya's technical skills encompass a wide range of programming languages, such as Python and R, along with proficiency in several tools and technologies. He has project experience in optimizing neural networks and served as a visualization analyst at Fractal Analytics, where he became the single point of contact for Procter & Gamble’s Image Recognition team. His advanced analytical skills will allow him to analyze and interpret data related to environmental factors, identify patterns and trends, and draw meaningful insights from data relevant to environmental conditions in DC.

Nina Ebensperger, also an MS student in the GW Data Science Department, serves as the lead researcher on the problem of large-scale eco-labeling. With relevant coursework in data warehousing, data mining, and algorithm design, Nina will utilize her experiences at GW to extract and analyze data from eco-labeling regimes. Her work experience in research and analysis roles, where she conducted data analysis, optimized workflows, and generated databases, highlights her practical experience in dealing with complex data and problem-solving. Nina's strong academic background, technical skills, and relevant work experience make her well-qualified to tackle the problem identification and quantification of existing eco-labeling regimes. 

Emily Fugh, a BA student studying Data Science and Finance, will provide all other research support throughout the summer.  Emily's skills in programming languages such as Python, SQL, and R, combined with her proficiency in tools like Tableau, make her well-equipped to navigate and synthesize information from academic and industry sources. Moreover, her involvement in various student associations and leadership roles highlights her organizational and communication skills, which are essential for conducting thorough literature reviews.

DSSD GW is fortunate to have these three students supporting important research that will address a key issue in eco-labeling: locational discrepancies in the environmental standards needed to ensure all labeled products and services are truly deserving of an eco-label. We will be providing continuous updates on our progress throughout summer and fall 2023.